Widi Aribowo, R. Rahmadian, M. Widyartono, A. Wardani, Aditya Prapanca, L. Abualigah
{"title":"Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer","authors":"Widi Aribowo, R. Rahmadian, M. Widyartono, A. Wardani, Aditya Prapanca, L. Abualigah","doi":"10.11591/ijpeds.v15.i2.pp696-703","DOIUrl":null,"url":null,"abstract":"In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.","PeriodicalId":355274,"journal":{"name":"International Journal of Power Electronics and Drive Systems (IJPEDS)","volume":"24 14","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power Electronics and Drive Systems (IJPEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijpeds.v15.i2.pp696-703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.